Forum Discussion
Data Ingestion to Fabric SQL Database
Hi Stat,
Thank you for posting your query in the Microsoft Fabric Community Forum.
Based on the official Microsoft Fabric documentation, loading data into a SQL database using Data Factory pipelines or copy activities requires that the SQL database is properly accessible within the same Fabric workspace and capacity context where the pipeline is executed.
The NotFound / ItemNotFound / FabricSqlConnectionInfo errors you are encountering typically indicate that the SQL database item is not being successfully resolved by Fabric services during pipeline execution. While you are able to connect through SSMS, this only validates T-SQL connectivity to the SQL endpoint. Data Factory pipelines additionally depend on Fabric service-level metadata and item resolution within the workspace.
According to Microsoft documentation:
- The workspace must be assigned to a Fabric capacity for Data Factory operations involving Fabric items.
• Data pipelines interact with Fabric items (such as SQL databases) through workspace-scoped artifacts, and correct workspace association is required.
• SQL database in Fabric has certain limitations and evolving capabilities, which can impact ingestion scenarios depending on configuration and readiness.
In scenarios where the same workflow works in a Fabric Trial but not in another capacity, this is typically related to differences in workspace configuration, item state, or feature enablement rather than the capacity SKU itself.
you may consider:
- Verifying that the SQL database, pipeline, and workspace are all within the same Fabric-enabled capacity
- Revalidating the SQL database selection in the pipeline (to ensure correct item reference)
- Confirming that the workspace region and configuration support SQL database ingestion scenarios
You can refer to the following official documentation for more details:
Limitations for SQL database - Microsoft Fabric | Microsoft Learn
Load data with pipelines into SQL database - Microsoft Fabric | Microsoft Learn
Thanks, lbendlin for sharing valuable insights.
Best regards,
Ganesh Singamshetty